Student teacher ratios

Area Facet

Photo by Greg Schneider on Unsplash

A teacher affects eternity: he can never tell where his influence stops…
— Henry Adams

Ingest

by country, year, and ratio

# Load csv data file
df <- read.csv("archetypes/student-teacher-ratios/student-teacher-ratios.csv", header = TRUE, stringsAsFactors = FALSE, encoding = "UTF-8")
df

Wrangle

wide to long

df_wrangle <- melt(df, id.vars=c("Country", "type"))
df_wrangle$variable <- as.integer(gsub("X", "", df_wrangle$variable))
df_wrangle

Wrangle

enrich with country code, continent, and region

df_wrangle <- df_wrangle %>% 
  filter(type == "Countries") %>% 
  mutate(country_code = countrycode(Country, "country.name", "iso3c")) %>% 
  mutate(region = countrycode(country_code, "iso3c", "un.regionsub.name")) %>% 
  mutate(continent = countrycode(country_code, "iso3c", "continent")) %>% 
  filter(!is.na(region)) %>%
  mutate(year = variable) %>%
  mutate(ratio = value)

df_wrangle

Analytics

aggregate by group (continent and region)

df_region <- df_wrangle %>% 
  group_by(year, region, continent) %>% 
  summarize(ratio = mean(ratio, na.rm = TRUE)) %>% 
  filter(!is.nan(ratio))

df_region

df_continent <- df_wrangle %>% 
  group_by(year, continent) %>% 
  summarize(ratio = mean(ratio, na.rm = TRUE)) %>% 
  filter(!is.nan(ratio))

# df_continent

Plot

facet by continent

theme_opts <- theme(
    text = element_text(family = "inconsolata", size = 10), 
    plot.title = element_text(color = "black", size = 16, face = "bold"),
    plot.subtitle = element_text(color = "black", size = 12),
    plot.caption = element_text(color = "#555555", size = 10),
    panel.border = element_blank(),
    panel.background = element_blank(),
    legend.position='none',
    panel.spacing.x = unit(1, "lines"),
    panel.spacing.y = unit(1, "lines"),
    panel.grid.minor = element_blank(),
    strip.text = element_text(size = 8.5, face = "bold"),
    strip.background = element_blank()
)

continent_palette <- c(
  "Asia" = "#171635",
  "Europe" = "#00225D",
  "Africa" = "#763262",
  "Oceania" = "#CA7508",
  "Americas" = "#E9A621"
)

# Plot
v1 <- ggplot(df_continent, aes(x = year, y = ratio, color = continent, fill = continent)) +
  geom_area(alpha = 0.5) +
  # geom_vline(aes(xintercept = year), size = 0.1, color = "gray80") +
  facet_wrap( ~ continent, ncol = 1) +
  scale_x_continuous(breaks = seq(1970, 2020, by = 10)) +
  scale_color_manual(values = continent_palette) +
  scale_fill_manual(values = continent_palette) +
  labs(title = "Student Teacher Ratios",
       subtitle = "by continent",
       caption = "Source: UNESCO Institute of Statistics",
       x = NULL,
       y = NULL) +
  theme_bw() +
  theme_opts

girafe(ggobj = v1, width_svg = 1080/72, height_svg = 720/72,
       options = list(opts_sizing(rescale = FALSE, width = 0.75))
)

Plot

facet by region

list_of_continents <- c("Africa", "Americas", "Asia", "Europe", "Oceania")

p1 <- ggplot(data = subset(df_region, continent == list_of_continents[[1]] ), aes(x = year, y = ratio, color = continent, fill = continent)) +
  geom_area(alpha = 0.5) +
  facet_wrap( ~ region, nrow = 1) +
  scale_x_continuous(breaks = seq(1970, 2020, by = 10)) +
  scale_color_manual(values = continent_palette) +
  scale_fill_manual(values = continent_palette) +
  labs(x = NULL,
       y = NULL,
       title = list_of_continents[[1]]) +
  theme_bw() +
  theme_opts

p2 <- ggplot(data = subset(df_region, continent == list_of_continents[[2]] ), aes(x = year, y = ratio, color = continent, fill = continent)) +
  geom_area(alpha = 0.5) +
  facet_wrap( ~ region, nrow = 1) +
  scale_x_continuous(breaks = seq(1970, 2020, by = 10)) +
  scale_color_manual(values = continent_palette) +
  scale_fill_manual(values = continent_palette) +
  labs(x = NULL,
       y = NULL,
       title = list_of_continents[[2]]) +
  theme_bw() +
  theme_opts

p3 <- ggplot(data = subset(df_region, continent == list_of_continents[[3]] ), aes(x = year, y = ratio, color = continent, fill = continent)) +
  geom_area(alpha = 0.5) +
  facet_wrap( ~ region, nrow = 1) +
  scale_x_continuous(breaks = seq(1970, 2020, by = 10)) +
  scale_color_manual(values = continent_palette) +
  scale_fill_manual(values = continent_palette) +
  labs(x = NULL,
       y = NULL,
       title = list_of_continents[[3]]) +
  theme_bw() +
  theme_opts

p4 <- ggplot(data = subset(df_region, continent == list_of_continents[[4]] ), aes(x = year, y = ratio, color = continent, fill = continent)) +
  geom_area(alpha = 0.5) +
  facet_wrap( ~ region, nrow = 1) +
  scale_x_continuous(breaks = seq(1970, 2020, by = 10)) +
  scale_color_manual(values = continent_palette) +
  scale_fill_manual(values = continent_palette) +
  labs(x = NULL,
       y = NULL,
       title = list_of_continents[[4]]) +
  theme_bw() +
  theme_opts

p5 <- ggplot(data = subset(df_region, continent == list_of_continents[[5]] ), aes(x = year, y = ratio, color = continent, fill = continent)) +
  geom_area(alpha = 0.5) +
  facet_wrap( ~ region, nrow = 1) +
  scale_x_continuous(breaks = seq(1970, 2020, by = 10)) +
  scale_color_manual(values = continent_palette) +
  scale_fill_manual(values = continent_palette) +
  labs(x = NULL,
       y = NULL,
       title = list_of_continents[[5]]) +
  theme_bw() +
  theme_opts

girafe(code = print(p1 / p2 / p3 / p4 / p5), width_svg = 1080/72, height_svg = 720/72,
       options = list(opts_sizing(rescale = FALSE, width = 0.75))
)

References

citations for narrative and data sources

Narrative: Jake Kaupp, TidyTuesday, https://github.com/jkaupp/tidytuesdays/tree/master/2019/week19
Data Source: UNESCO Institute of Statistics